damiansm
damiansm
Genome Med paper that describes the classical genes that are enriched for variants and to be treated with caution for genuine size-reason e.g. TTN and mis-aligned e.g. MUC16
Recent studies highlight many patients can have more than one diagnosis e.g. 5% observed at the Baylor diagostic lab: https://www.nejm.org/doi/10.1056/NEJMoa1516767?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dwww.ncbi.nlm.nih.gov Phenotype similarity algorithms can potentially identify this scenario and in...
Diagnostic-grade Exomiser with a manually curated source of reliable disease-gene associations i.e. like what we do for Genomics England with PanelApp. The trouble is no-one has this knowledgebase yet and...
Peter knows Tommasso Pippucci pretty well (see https://www.ncbi.nlm.nih.gov/pubmed/?term=pippucci+t+homozygosity) so could implement his algorithms within Exomiser and just limit the phenotype search within the autozgosity intervals.
Should we somehow have a disease-level age of onset filter one day i.e. if we know the genome is from a newborn don't highlight a phenotype match based on Parkinson's...
With our current implementation the scores for PPI hits to direct StringDB interactors don't end up much above those to quite distant interactors in the network. This is not clear...
Bringing in where the variant is located in terms of PPI into the prioritisation. There were some cool talks a few years back at ASHG on how this can really...
https://www.biorxiv.org/content/10.1101/554444v1?rss=1
missense tolerance ratio (MTR) uses GNOMAD data to assess whether certain regions of proteins are susceptible to disease-causing missense variants. - http://mtr-viewer.mdhs.unimelb.edu.au/ - https://genome.cshlp.org/content/27/10/1715 Assess whether this score will improve...
In terms of missense pathogenicity prediction scores, we have already benchmarked several second generation methods in our existing frameworks to establish whether they improved over the existing method of taking...